Use the technology at hand to ensure maintenance efficiency
Define, enforce preventive maintenance guidelines
Somewhere along the spectrum of maintenance strategies—from problem-of-the-moment to full predictive maintenance—is daily reality, for each plant. But that’s where the similarity ends, since no two plants are alike when it comes to equipment/loading, operational cycles, staff, skill sets, and budget.
While operational definitions of “efficiency” and “productivity” are set at the local level, practices and tactics for achieving those states can be leveraged from the collective whole. Putting the ideal state of full predictive maintenance aside, here are the tenets for a preventive maintenance program.
- Identifies the most important equipment in a plant, where importance can be defined by cost of equipment, cost of downtime, or cost of ruined output
- Identifies which data points (measurements) are early indicators of changes in performance health
- Schedule for equipment inspection
- Standard process for taking, comparing, and storing measurement data
- Process for acting upon early warning signs.
Both approaches involve inspecting key equipment at regular intervals; the difference comes in to how the data is used. Predictive maintenance or reliability professionals are typically better trained on more specialized subjects and use more advanced programs to collect, track, and analyze data. A smaller maintenance team at small or mid-sized industrial facility typically knows its equipment, does some amount of scheduled maintenance, has strong troubleshooting skills, and has a team lead.
Bottlenecks occur when the team has to transfer measurement information from the job at hand into a larger “system”—which usually involves data entry—and in accessing that information on the fly. In reality, a lot of the equipment knowledge, status, and assessment skills are stored in individual heads.
Ironically, the thing that is enabling plants to get ahead of this curve came from outside of the facilities maintenance industry. It’s the personal smartphone/tablet that the majority of maintenance professionals carry. Smartphone apps connected to both wireless measurement tools and cloud-based maintenance databases leverage existing cell phone and test tool skills, are instantly accessible from just about any location, and fill the gaps in the existing process.
These smart tools turn data that was previously taken at the moment but never recorded, and leverages it into a longer term opportunity by collecting important data points from each machine, entering them into a database in the cloud, and thus establishing a history of the specific machine.
Techs can then access those previous measurements the next time they’re on-site, compare to a baseline, and check if there’s a trend-to-the-worse in performance indicators. The same previous measurements are also very helpful in troubleshooting.
Not all members of the team may be trained on baselines, early indicators, and the other basic tenets of preventive maintenance. When implementing smart-tool based maintenance, consider the following:
1. Hold lunch-and-learns for the team on the tell-tales and the objectives so everyone knows what to look for and feels part of the mission.
- Provide some basic how-to on using the app and measurement look-up. This helps anyone who is uncomfortable using the technology to learn what to do without feeling embarrassed.
- Share the data logs every quarter and explain what the measurements tell you. This kind of “reason-why” is more meaningful in the context of your own equipment than in the abstract. Help people understand their work makes a difference.
2. Appoint a “champion” who checks the data share on a semi-regular basis and looks for changes that might indicate a problem. (In general, when measurements start to deviate by 5% or 10%, it’s time to investigate.)
- Management should be responsible for maintaining, checking, and assessing the data.
- The team should be enabled and encouraged to check the log on the job, not just for data entry; also to check the data history on that system whenever they enter a troubleshooting situation.
3. Set up incentives for the team to:
- Speak up if they see something that might fall into a tell-tale category.
- Think of other ways to use the cloud log and data sharing to improve team communication.
Here’s why it works:
People like using their smartphones so much, they are more willing to enter data if they can use their device to do it. It’s still a two-step process (1. Take measurement, 2. Save to equipment record in cloud), but it’s better than the old three-step involving handwritten notes and data entry back at the office, and the equipment record does double-duty as a routing tool.
Proactive maintenance measurements aren’t that different from troubleshooting tests. You’re looking for signs of potential failure, so you take measurements related to failure modes, and record them.
Additional option: Leave-behind monitoring
As teams start to add proactive maintenance to their thinking, it becomes clear that not every large system in the facility needs active monitoring all of the time. The pinch point comes when a machine or some of its key components start to degrade. At that point maintenance needs to order parts, schedule downtime as needed, and check the system more often. To reduce the time required for those stepped-up inspections, some teams have started to use small leave-behind mini-meters that can be locked into the panel and send data wirelessly to a master meter or computer.
As techs adapt to saving their measurements to the database and using apps to share troubleshooting information and approvals, skills start to transfer—between individuals and to the organization as a whole. Each reduction in the “churn” caused by firefighting creates more time for preventive maintenance activities, creating a new “operational reality.”
Leah Friberg is education and public affairs manager for Fluke Corporation.